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Enhanced Bayesian Network Models for Spatial Time Series Prediction

Recent Research Trend in Data-Driven Predictive Analytics

  • Monidipa Das
  • Soumya K. Ghosh
Book

Part of the Studies in Computational Intelligence book series (SCI, volume 858)

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Monidipa Das, Soumya K. Ghosh
    Pages 1-9
  3. Monidipa Das, Soumya K. Ghosh
    Pages 23-52
  4. Monidipa Das, Soumya K. Ghosh
    Pages 53-79
  5. Monidipa Das, Soumya K. Ghosh
    Pages 81-99
  6. Monidipa Das, Soumya K. Ghosh
    Pages 101-113
  7. Monidipa Das, Soumya K. Ghosh
    Pages 137-142
  8. Back Matter
    Pages 143-149

About this book

Introduction

This research monograph is highly contextual in the present era of spatial/spatio-temporal data explosion. The overall text contains many interesting results that are worth applying in practice, while it is also a source of intriguing and motivating questions for advanced research on spatial data science. 
The monograph is primarily prepared for graduate students of Computer Science, who wish to employ probabilistic graphical models, especially Bayesian networks (BNs), for applied research on spatial/spatio-temporal data. Students of any other discipline of engineering, science, and technology, will also find this monograph useful. Research students looking for a suitable problem for their MS or PhD thesis will also find this monograph beneficial. The open research problems as discussed with sufficient references in Chapter-8 and Chapter-9 can immensely help graduate researchers to identify topics of their own choice. The various illustrations and proofs presented throughout the monograph may help them to better understand the working principles of the models. The present monograph, containing sufficient description of the parameter learning and inference generation process for each enhanced BN model, can also serve as an algorithmic cookbook for the relevant system developers.

Keywords

Spatio-temporal data Spatial time series prediction Applied machine learning Computational Intelligence Advanced Bayesian Network Graph-based Model Probabilistic Reasoning Parameter Learning Bayesian Inference Computational Complexity

Authors and affiliations

  • Monidipa Das
    • 1
  • Soumya K. Ghosh
    • 2
  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology KharagpurKharagpurIndia
  2. 2.Department of Computer Science and EngineeringIndian Institute of Technology KharagpurKharagpurIndia

Bibliographic information

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